Reduced order models (ROMs) aim to exploit underlying, low-dimensional patterns of spatio-temporal activity in order to promote improved understanding of the systems as well as computational efficiency. Critical to the successful implementation of a reduced order model scheme is the ability to interpolate the nonlinear contributions to the dynamical evolution. This was recognized early in ROM computational schemes and a suite of methods, broadly termed gappy POD methods, have been developed in order to provide interpolation methodologies for producing efficient, low-dimensional ROMs.
